sklearn_pmml_model.neighbors

The sklearn.neighbors module implements the k-nearest neighbors algorithm.

Submodules

• sklearn_pmml_model.neighbors._base
• sklearn_pmml_model.neighbors._classes

Package Contents

Classes

PMMLKNeighborsClassifier	Classifier implementing the k-nearest neighbors vote.
PMMLKNeighborsRegressor	Regression based on k-nearest neighbors.

class sklearn_pmml_model.neighbors.PMMLKNeighborsClassifier(pmml, n_jobs=None)

Bases: sklearn_pmml_model.base.PMMLBaseClassifier, sklearn_pmml_model.neighbors._base.PMMLBaseKNN, sklearn.neighbors.KNeighborsClassifier

Classifier implementing the k-nearest neighbors vote.

Parameters:

pmmlstr, object

Filename or file object containing PMML data.

n_jobsint, default=None

The number of parallel jobs to run for neighbors search. None means 1 unless in a joblib.parallel_backend context. -1 means using all processors. See Glossary for more details. Doesn’t affect fit() method.

Notes

Specification: http://dmg.org/pmml/v4-3/KNN.html

fit(x, y)

Not supported: PMML models are already fitted.

_more_tags()

class sklearn_pmml_model.neighbors.PMMLKNeighborsRegressor(pmml, n_jobs=None)

Bases: sklearn_pmml_model.base.PMMLBaseRegressor, sklearn_pmml_model.neighbors._base.PMMLBaseKNN, sklearn.neighbors.KNeighborsRegressor

Regression based on k-nearest neighbors.

The target is predicted by local interpolation of the targets associated of the nearest neighbors in the training set.

Parameters:

pmmlstr, object

Filename or file object containing PMML data.

n_jobsint, default=None

The number of parallel jobs to run for neighbors search. None means 1 unless in a joblib.parallel_backend context. -1 means using all processors. See Glossary for more details. Doesn’t affect fit() method.

Notes

Specification: http://dmg.org/pmml/v4-3/KNN.html

fit(x, y)

Not supported: PMML models are already fitted.

_more_tags()